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NIR Spectra (nir + spectrum)
Selected AbstractsA physiochemical theory on the applicability of soft mathematical models,experimentally interpretedJOURNAL OF CHEMOMETRICS, Issue 7-8 2010L. Munck Abstract An extension of chemometric theory was experimentally explored to explain the physiochemical basis of the very high efficiency of soft modelling of data from nature. Soft modelling in self-organisation was interpreted by studying the unique chemical patterns of mutants in an isogenic barley model on endosperm development. Extremely reproducible, differential Near Infrared (NIR) spectral patterns specifically overviewed the effect on cell composition of each mutant cause. Extended Canonical Variates Analysis (ECVA) classified spectra in wild type, starch and protein mutants. The spectra were interpreted by chemometric data analysis and by pattern inspection to morphological, genetic, molecular and chemical information. Deterministic chemical reactions were defined in the glucan pathway. A drastic mutation in a gene controlling the starch/ß-glucan composition changed water activity that introduced a diffusive, stochastic effect on the catalysis of all active enzymes. ,Decision making' in self-organisation is autonomous and performed by the soft modelling of the chemical deterministic and stochastic reactions in the endosperm cell as a whole. Uncertainty in the analysis of endosperm emergence was experimentally delimited as the ,indeterminacy' in local molecular path modelling ,bottom up' and the ,irreducibility' of the phenomenological NIR spectra ,top down'. The experiment confirmed Ilya Prigogine's interpretation of self-organisation by his dynamic computer model programmed with a self-modeled non-local extension of quantum mechanics (QM). The significance of self- organisation explained by Prigogine here interpreted as physiochemical soft modelling introduces a paradigm shift in macroscopic science that forwards a major argument for soft mathematical modelling and chemometrics to obtain full scientific legitimacy. Copyright © 2010 John Wiley & Sons, Ltd. [source] Optimizing the tuning parameters of least squares support vector machines regression for NIR spectraJOURNAL OF CHEMOMETRICS, Issue 5 2006T. Coen Abstract Partial least squares (PLS) is one of the most used tools in chemometrics. Other data analysis techniques such as artificial neural networks and least squares support vector machines (LS-SVMs) have however made their entry in the field of chemometrics. These techniques can also model nonlinear relations, but the presence of tuning parameters is a serious drawback. These parameters balance the risk of overfitting with the possibility to model the underlying nonlinear relation. In this work a methodology is proposed to initialize and optimize those tuning parameters for LS-SVMs with radial basis function (RBF)-kernel based on a statistical interpretation. In this way, these methods become much more appealing for new users. The presented methods are applied on manure spectra. Although this dataset is only slightly nonlinear, good results were obtained. Copyright © 2007 John Wiley & Sons, Ltd. [source] Hyperspectral NIR image regression part II: dataset preprocessing diagnosticsJOURNAL OF CHEMOMETRICS, Issue 3-4 2006James Burger Abstract When known reference values such as concentrations are available, the spectra from near infrared (NIR) hyperspectral images can be used for building regression models. The sets of spectra must be corrected for errors, transformed to reflectance or absorbance values, and trimmed of bad pixel outliers in order to build robust models and minimize prediction errors. Calibration models can be computed from small (<100) sets of spectra, where each spectrum summarizes an individual image or spatial region of interest (ROI), and used to predict large (>20,000) test sets of spectra. When the distributions of these large populations of predicted values are viewed as histograms they provide mean sample concentrations (peak centers) as well as uniformity (peak widths) and purity (peak shape) information. The same predicted values can also be viewed as concentration maps or images adding spatial information to the uniformity or purity presentations. Estimates of large population statistics enable a new metric for determining the optimal number of model components, based on a combination of global bias and pooled standard deviation values computed from multiple test images or ROIs. Two example datasets are presented: an artificial mixture design of three chemicals with distinct NIR spectra and samples of different cheeses. In some cases it was found that baseline correction by taking first derivatives gave more useful prediction results by reducing optical problems. Other data pretreatments resulted in negligible changes in prediction errors, overshadowed by the variance associated with sample preparation or presentation and other physical phenomena. Copyright © 2007 John Wiley & Sons, Ltd. [source] Rapid estimation of chemical kinetics by implicit calibration.JOURNAL OF CHEMOMETRICS, Issue 2 2003Abstract This study continues the development of a method, implicit calibration, for estimating kinetic parameters from on-line measurements of batch reactions. The basic idea of implicit calibration is to combine non-linear parameter estimation with the calibration of measured spectra with concentrations calculated by an assumed kinetic model. A new example is studied, an esterification reaction with a rather complicated kinetic mechanism, where activities, instead of concentrations, and NIR spectra are used as measurements. The emphasis in the study is on estimating the uncertainty of the kinetic parameters. Two approaches, linearization and bootstrap, are applied. In the case studied, the two approaches give closely similar estimates of the uncertainty. As well, a new way is introduced to control the rigidity of the implicit calibration, based on minimizing the lack of fit of the model. It is also shown that ,mixed implicit calibration', i.e. implicit calibration combined with a few off-line calibrated concentrations, greatly enhances the identifiability of the kinetic model. Copyright © 2003 John Wiley & Sons, Ltd. [source] A near-infrared spectroscopic investigation of relative density and crushing strength in four-component compactsJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 3 2009Steven M. Short Abstract Near-infrared spectroscopy (NIRS) is commonly employed for the analysis of chemical and physical attributes of intact pharmaceutical compacts. Specifically, NIRS has proven useful in the nondestructive measurement of tablet hardness or crushing strength. Near-infrared (NIR) reflectance and transmittance spectra were acquired for 174 13-mm compacts, which were produced according to a four-constituent mixture design (29 points) composed of anhydrous theophylline, lactose monohydrate, microcrystalline cellulose, and soluble starch. Six compacts were produced for each design point by compacting at multiple pressures. Physical testing and regression analyses were used to model the effect of variation in relative density (and crushing strength) on NIR spectra. Chemometric analyses demonstrated that the overall spectral variance was strongly influenced by anhydrous theophylline as a result of the experimental design and the component's spectroscopic signature. The calibration for crushing strength was more linear than the relative density model, although accuracy was poorer in comparison to the density model due to imprecision of the reference measurements. Based on the consideration of reflectance and transmittance measurements, a revised rationalization for NIR sensitivity to compact hardness is presented. © 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:1095,1109, 2009 [source] Dehydration studies using a novel multichamber microscale fluid bed dryer with in-line near-infrared measurementJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 10 2003Eetu Räsänen Abstract The purpose of this research was to study the effect of two process parameters (temperature and moisture content) on dehydration behavior of different materials using a novel multichamber microscale fluid bed dryer with a process air control unit and in-line near-infrared (NIR) spectroscopy. The materials studied were disodium hydrogen phosphates with three different levels of hydrate water and wet theophylline granules. Measured process parameters of fluid bed drying were logged, including in-line NIR signals. Off-line analyses consisted of X-ray powder diffraction patterns, Fourier transform NIR spectra and moisture contents of studied materials. During fluid bed drying, the stepwise dehydration of materials was observed by the water content difference of inlet and outlet air, the pressure difference over the bed, and the in-line NIR spectroscopy. The off-line analysis confirmed the state of solid materials. The temperature and the moisture content of the process air were demonstrated to be significant factors for the solid-state stability of theophylline. The presented setup is a material and cost-saving approach for studying the influence of different process parameters on dehydration behavior during pharmaceutical processing. © 2003 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 92:2074,2081, 2003 [source] In-Line Monitoring of Vinyl Chloride Suspension Polymerization with Near-Infrared Spectroscopy, 1 , Analysis of Morphological PropertiesMACROMOLECULAR REACTION ENGINEERING, Issue 1 2010João Miguel de Faria Jr. Abstract It is demonstrated that during suspension polymerizations it is possible to monitor morphological characteristics of PVC resins such as bulk density, cold plasticizer absorption and average particle diameter in-line and in real time using NIR spectroscopy. NIR spectra are obtained at different experimental conditions, showing that the spectra are sensitive to changes in the PVC properties. Standard mathematical procedures (partial least squares regression) are used to build empirical models and correlate the morphological properties with the obtained NIR spectra, allowing for monitoring of the PVC morphology in-line and in real time. [source] Near-infrared analysis of fennel (Foeniculum vulgare Miller) on different spectrometers,basic considerations for a reliable networkPHYTOCHEMICAL ANALYSIS, Issue 5 2003Boris Steuer Abstract The aim of this study was to investigate the accuracy and transferability of near-infrared (NIR) calibrations for estimating the content and composition of the volatile fraction in fennel fruits (Foeniculum vulgare Miller) as an example of medicinal and spice plants. A master calibration with spectra obtained on a scanning monochromator was generated using 345 samples from three different harvests (1997,1999). A subset of 70 samples from 1999 was also measured on a dispersive grating and a scanning diode array system to gain an insight into the in,uence of sample presentation and scanning techniques. For all instruments, calibrations with standard errors in the range of the reference method were achieved. Furthermore the in,uence of storage on NIR spectra and, additionally, the potential of transferring spectra between both scanning monochromators was studied. Copyright © 2003 John Wiley & Sons, Ltd. [source] Rapid techniques for assessing fibre quality of flax breeding lines and cultivars using visible and near infrared spectroscopy, and thermal analysisANNALS OF APPLIED BIOLOGY, Issue 2 2006Z. Jankauskien Abstract Fifteen different flax cultivars and breeding lines (E-68, Baltu,iai, Belinka, Vega 2, Ilona, Elise, Kasty,iai, Evelin, 1963-3, Ariane, Hermes, 01057-12, 1698-13a, 2017-3, 1864-24) were cultivated, harvested, water-retted, scutched and resulting fibres passed through pin frames to produce representative samples for each variety. The aim of this investigation was to develop rapid techniques for assessing quality of fibre obtained from a comparative agronomical trial. The fibres produced were then assessed using visible and near infrared spectroscopy (Vis,NIRS), thermal analysis, scanning electron microscopy and airflow method for measuring fibre fineness. The relationships between agronomical characteristics, fibre fineness, thermal and spectral results were assessed using principal component analysis and partial least squares regression methods. The micrographs of the samples revealed the presence of residual pectic and cuticular tissues on all fibres, and significant differences between the 15 fibre samples were not observed. A significant relationship of the differences in fibre fineness of the test samples as measured by airflow method and Vis,NIR spectra was observed with an R2 of 0.97 and standard error of calibration (SEC) of 1.69 dtex, and the former parameter also correlated with the measured thermal combustion parameters showing an R2 of 0.91 and SEC of 2.86 dtex, indicating that the two rapid techniques could be used for the assessment of fibre quality of selected plants from the breeding programme. The advantages of using the two instrumental techniques compared with the existing airflow method are briefly discussed. [source] Application of near-infrared (NIR) spectroscopy for screening of raw materials used in the cell culture medium for the production of a recombinant therapeutic proteinBIOTECHNOLOGY PROGRESS, Issue 2 2010Alime Ozlem Kirdar Abstract Control of raw materials based on an understanding of their impact on product attributes has been identified as a key aspect of developing a control strategy in the Quality by Design (QbD) paradigm. This article presents a case study involving use of a combined approach of Near-infrared (NIR) spectroscopy and Multivariate Data Analysis (MVDA) for screening of lots of basal medium powders based on their impact on process performance and product attributes. These lots had identical composition as per the supplier and were manufactured at different scales using an identical process. The NIR/MVDA analysis, combined with further investigation at the supplier site, concluded that grouping of medium components during the milling and blending process varied with the scale of production and media type. As a result, uniformity of blending, impurity levels, chemical compatibility, and/or heat sensitivity during the milling process for batches of large-scale media powder were deemed to be the source of variation as detected by NIR spectra. This variability in the raw materials was enough to cause unacceptably large variability in the performance of the cell culture step and impact the attributes of the resulting product. A combined NIR/MVDA approach made it possible to finger print the raw materials and distinguish between good and poor performing media lots. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010 [source] In situ near infrared spectroscopy for analyte-specific monitoring of glucose and ammonium in streptomyces coelicolor fermentationsBIOTECHNOLOGY PROGRESS, Issue 1 2010Nanna Petersen Abstract There are many challenges associated with in situ collection of near infrared (NIR) spectra in a fermentation broth, particularly for highly aerated and agitated fermentations with filamentous organisms. In this study, antibiotic fermentation by the filamentous bacterium Streptomyces coelicolor was used as a model process. Partial least squares (PLS) regression models were calibrated for glucose and ammonium based on NIR spectra collected in situ. To ensure that the models were calibrated based on analyte-specific information, semisynthetic samples were used for model calibration in addition to data from standard batches. Thereby, part of the inherent correlation between the analytes could be eliminated. The set of semisynthetic samples were generated from fermentation broth from five separate fermentations to which different amounts of glucose, ammonium, and biomass were added. This method has previously been used off line but never before in situ. The use of semisynthetic samples along with validation on an independent batch provided a critical and realistic evaluation of analyte-specific models based on in situ NIR spectroscopy. The prediction of glucose was highly satisfactory resulting in a RMSEP of 1.1 g/L. The prediction of ammonium based on NIR spectra collected in situ was not satisfactory. A comparison with models calibrated based on NIR spectra collected off line suggested that this is caused by signal attenuation in the optical fibers in the region above 2,000 nm; a region which contains important absorption bands for ammonium. For improved predictions of ammonium in situ, it is suggested to focus efforts on enhancing the signal in that particular region. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010 [source] | |||||||||||||